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generate-docs.py learns the agent-launcher domain (5 hardcoded maps extended); regenerated docs tree: 343 skill pages / 96 agent pages / 122 command pages (561 total). mkdocs.yml nav gains the Agent Launcher skill section (7 pages), 4 cs-agent-* agent entries, and 8 /cs:* command entries; all nav targets verified to exist. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012FwXG6TqCXKZQvF4iD69cv
67 lines
3.3 KiB
Markdown
67 lines
3.3 KiB
Markdown
---
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title: "/cs-deep-research — Slash Command for AI Coding Agents"
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description: "/cs:deep-research <question> — Disciplined multi-source investigation for a high-stakes question. Reframes into falsifiable hypotheses, plans, fans. Slash command for Claude Code, Codex CLI, Gemini CLI."
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---
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# /cs-deep-research
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<div class="page-meta" markdown>
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<span class="meta-badge">:material-console: Slash Command</span>
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<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/2-claude-skills/tree/main/research/deep-research/commands/cs-deep-research.md">Source</a></span>
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</div>
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**Command:** `/cs:deep-research <question>`
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The `cs-deep-research` persona turns "research this" into an auditable, reusable investigation — the workflow to reach for when getting the answer *wrong* costs more than the tokens spent getting it right.
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## When to Run
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- A low-quality answer is expensive: strategy, business plan, report, or article groundwork.
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- Comparing N institutions / products / methods / markets with defensible reasoning.
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- Validating a hypothesis or an irreversible decision against external data.
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- Meta-research: "understand how X works," "map the landscape of Y."
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## When NOT to Run
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- Quick fact-checks → answer directly.
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- Structured 12-dimension competitor scoring → `competitive-teardown`.
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- Fast topic overviews where decision risk is low → the **research router** (`/cs:research`).
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## What You Get
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1. **Reframe** — the question rewritten to the real decision + 2-4 falsifiable hypotheses.
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2. **`plan.md`** — genre, sourcing strategy, opposition queries, risk register, stop-criteria.
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3. **Parallel search** — sub-agents fanned out across channels; each source saved to `sources/NN_slug.md` with verbatim quotes + Credibility/Recency/Bias scores.
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4. **Triangulated synthesis** — every thesis backed by >=3 independent, differently-typed sources (or flagged "insufficient evidence"), plus a mandatory adversarial pass.
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5. **A reusable folder** — `sources.csv`, `findings/`, final report, and `refresh_targets.md` for delta-updates later.
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## Trigger Phrases (auto-invoke without /cs:)
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- "deep research on [topic]" / "do a deep dive on [topic]"
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- "research this thoroughly / rigorously" / "high-stakes research"
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- "compare [N options] and give me defensible reasoning"
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- "validate this hypothesis with external data"
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## Discipline
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- **No fabricated citations** — empty fetch = empty claim.
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- **Triangulation mandatory** — < 3 independent, differently-typed sources → "insufficient evidence," not fact.
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- **Adversarial pass required** on medium/deep investigations.
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- **Parallel sub-agents** — never serial in the search phase.
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- **Persist to files** — the reuse value is the folder, not the transcript.
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## Stop Conditions
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- Report written + every thesis triangulated or flagged + `refresh_targets.md` emitted → done.
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- On an `update <slug>` run: produce a delta in `diffs/` instead of replaying the whole investigation.
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## Related
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- Agent: [`cs-deep-research`](https://github.com/alirezarezvani/claude-skills/tree/main/research/deep-research/agents/cs-deep-research.md)
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- Skill: [`deep-research`](https://github.com/alirezarezvani/claude-skills/tree/main/research/deep-research/skills/deep-research/SKILL.md)
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- Siblings: `/cs:pulse` (recency), the research router, `litreview` / `dossier` / `patent`
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---
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**Version:** 1.0.0
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